result (pandas.DataFrame) – data frame containing predictions per sample (in row). It must have a column of
true class named “Y_TRUE”. It must have a column of predicted class named “Y_PRED”
or multiple columns of predicted probabilities for each class. It typically takes
the output of classify().
normalize (bool) – normalize the confusion matrix or not
ax (matplotlib.axes.Axes or None (default), optional) – The axes where the confusion matrix is plotted. None (default) to create a new figure and
axes to plot the confusion matrix
classes (list) – The list of the labels you want to include in the plot in the order specified in the list.
kwargs (dict) – keyword argument passing to matplotlib.pyplot.imshow(). For example, you can pass
vmin=0, vmax=1 as keyword arguments to manually define color range (especially useful
when you set normalize=True)
